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Instruction 13-4
a Real Estate Builder Wishes to Determine How

question 158

Multiple Choice

Instruction 13-4
A real estate builder wishes to determine how house size (House) is influenced by family income (Income) ,family size (Size) ,and education of the head of household (School) .House size is measured in hundreds of square metres,income is measured in thousands of dollars,and education is in years.The builder randomly selected 50 families and ran the multiple regression.Microsoft Excel output is provided below:
OUTPUT
SUMMARY
Regression Statistics
 Multiple R 0.865 R Square 0.748 Adj. R Square 0.726 Std. Error 5.195 Observations 50 \begin{array}{ll}\text { Multiple R } & 0.865 \\ \text { R Square } & 0.748 \\ \text { Adj. R Square } & 0.726 \\ \text { Std. Error } & 5.195 \\ \text { Observations } & 50\end{array}
ANOVA
df SS  MS  F  Siguif F Regression 3605.7736901.44340.0001 Residual 1214.226426.9828 Total 494820.0000\begin{array}{llllll} & d f & \text { SS } & \text { MS } & \text { F } & \text { Siguif } \boldsymbol{F} \\\text { Regression } & & 3605.7736 & 901.4434 & & 0.0001 \\\text { Residual } & & 1214.2264 & 26.9828 & & \\\text { Total } & 49 & 4820.0000 & & &\end{array}

 Coeff  SttError t Stat P-value  Intercept 1.63355.80780.2810.7798 Income 0.44850.11373.95450.0003 Size 4.26150.80625.2860.0001 School 0.65170.43191.5090.1383\begin{array}{lllll} & \text { Coeff } & \text { SttError } & \boldsymbol{t} \text { Stat } & \boldsymbol{P} \text {-value } \\\text { Intercept } & -1.6335 & 5.8078 & -0.281 & 0.7798 \\\text { Income } & 0.4485 & 0.1137 & 3.9545 & 0.0003 \\\text { Size } & 4.2615 & 0.8062 & 5.286 & 0.0001 \\\text { School } & -0.6517 & 0.4319 & -1.509 & 0.1383\end{array} Note: Adj.R Square = Adjusted R Square;Std.Error = Standard Error
-Referring to Instruction 13-4,what are the residual degrees of freedom that are missing from the output?


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